1. Field of the Invention
The present invention generally relates to the identification and classification of sound sources and, more particularly, to detection and improvement of signal-to-noise ratio of otherwise undetectable harmonics and/or sub-harmonics of detectable but unstable tones.
2. Description of the Prior Art
The identification and classification of sound sources remains an important aspect of commercial and applied acoustics, particularly in regard to underwater environments where the opportunity for visual or other mechanisms for observation are very limited or lacking altogether. However, detection of sounds which may emanate from a sound source of interest usually requires isolation of sounds at a relatively low level from among relatively high levels of noise or sounds from other sources even though relatively few sound sources which are likely to be of interest are stable in frequency, phase or waveform and a relatively large amount of information and signal excess or detail is likely to be lost by filter mismatch relative to signal characteristics, particularly if stability of frequency is assumed.
When performing acoustic source classification or identification, it is important to identify tones with harmonic families and to identify as many harmonics as possible for each source. It is often the case that tones from different sources are close in frequency but differ in instability patterns or speed behavior. Speed behavior (e.g. variation in frequency due to load variations such as flow and density variation for a pump) that is only loosely coupled to the acoustic source is often encountered.
Techniques known as “order tracking” are known and have been used is the automobile industry to improve extraction and analysis of noise sources which are dependent on engine rotational speed as well as numerous other applications in other fields such as in adaptive filters and the like. As usually practiced, a basic feature of such techniques is to measure engine RPM, which will necessarily be slightly variable and unstable even when held as closely as possible to a constant rotational speed, and then re-sample a recording of captured noise at a sampling rate which corresponds accurately to the measured rotational speed. This, in effect, holds the apparent rotational speed to a constant value since the sampling rate tracks variations in the actual rotational speed. As a result, all of the hard coupled engine-related noises also appear to have a constant frequency in the re-sampled data and thus become much easier to detect, analyze and isolate. These applications are generally interested in signals having a high signal-to-noise ratio (SNR) in a relatively rich background of narrow band signals.
More generally, it is relatively easy for a trained analyst to identify lines (e.g. detected tones or spectral lines) in a signal which have the same instability pattern, assuming they have sufficient amplitude to be detected at all in a given noisy signal. Order tracking thus uses an external reference such as a tachometer to directly control the clock of an analog to digital (A/D) converter or, alternatively, to control re-sampling of a co-recorded digital signal (e.g. a tachometer output). Unless the reference is digitized at the same time as the acoustic signal to be processed or analyzed, aligning the signal to be processed or analyzed with the co-recorded signal presents significant technical challenges.
Thus order tracking is not applicable to a so-called “blind analysis” because it assumes a reference and that all signals of interest are related to the reference (e.g. a rotation rate of an engine); a condition which cannot be met with an unknown or non-cooperative acoustic signal source or when multiple acoustic signal sources are co-mingled into a single acoustic or vibration signal.
Further, order tracking, by its nature, is designed around significant change in frequency in a short period of time.
There are many marine sources which produce unstable tonals, including diesel engines, DC auxiliaries and most propulsion plants. Some AC auxiliaries also produce unstable tonals, such as induction motors which vary in rotational speed and electrically related sound emanations with changes in mechanical load. Land based machinery often exhibits similar characteristics. Additionally, other contributions to frequency instability may be caused by flows and thermal or density gradients in gas or liquid between the sound source and the sound detection apparatus, Doppler effects due to relative movement of the sound source and detection apparatus, reflections from fixed or moving surfaces in the environment and the like. Further, full analysis and classification or identification of sound sources generally requires relatively detailed matching of sound spectral content which is compromised if some spectral components of the sound are undetected or undetectable amid noise. Further, “order tracking” techniques generally rely upon detection or at least approximate knowledge or prior independent measurement of a fundamental frequency whereas, in classification or identification of an unknown sound source, the fundamental frequency may not only be unknown, but may be below the frequency range detectable by current equipment particularly sonar equipment in underwater applications.